Search

Background Rapid detection, isolation, and contact tracing of community COVID-19 cases are essential measures to limit the community spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to identify a parsimonious set of symptoms that jointly predict COVID-19 and investigated whether predictive symptoms differ between the B.1.1.7 (Alpha) lineage (predominating as of April 2021 in the US, UK, and elsewhere) and wild type. Methods and findings We obtained throat and nose swabs with valid SARS-CoV-2 PCR test results from 1,147,370 volunteers aged 5 years and above (6,450 positive cases) in the REal-time Assessment of Community Transmission-1 (REACT-1) study. This study involved repeated community-based random surveys of prevalence in England (study rounds 2 to 8, June 2020 to January 2021, response rates 22%–27%). Participants were asked about symptoms occurring in the week prior to testing. Viral genome sequencing was carried out for PCR-positive samples with N-gene cycle threshold value < 34 (N = 1,079) in round 8 (January 2021). In univariate analysis, all 26 surveyed symptoms were associated with PCR positivity compared with non-symptomatic people. Stability selection (1,000 penalized logistic regression models with 50% subsampling) among people reporting at least 1 symptom identified 7 symptoms as jointly and positively predictive of PCR positivity in rounds 2–7 (June to December 2020): loss or change of sense of smell, loss or change of sense of taste, fever, new persistent cough, chills, appetite loss, and muscle aches. The resulting model (rounds 2–7) predicted PCR positivity in round 8 with area under the curve (AUC) of 0.77. The same 7 symptoms were selected as jointly predictive of B.1.1.7 infection in round 8, although when comparing B.1.1.7 with wild type, new persistent cough and sore throat were more predictive of B.1.1.7 infection while loss or change of sense of smell was more predictive of the wild type. The main limitations of our study are (i) potential participation bias despite random sampling of named individuals from the National Health Service register and weighting designed to achieve a representative sample of the population of England and (ii) the necessary reliance on self-reported symptoms, which may be prone to recall bias and may therefore lead to biased estimates of symptom prevalence in England. Conclusions Where testing capacity is limited, it is important to use tests in the most efficient way possible. We identified a set of 7 symptoms that, when considered together, maximize detection of COVID-19 in the community, including infection with the B.1.1.7 lineage., Joshua Elliot, Matthew Whitaker, and colleagues investigate predictive symptoms for community COVID-19 cases in the REACT-1 study., Author summary Why was this study done? The rapid detection of SARS-CoV-2 infection in the community is key to ensuring efficient control of transmission via isolation. Eligibility for community PCR testing is determined based on the reported presence of several (predetermined) symptoms, which may vary from one country to another. Quantitative evidence measuring which symptoms are the most informative of a COVID-19 infection remains scarce. What did the researchers do and find? Data were collected from over 1 million participants in the REACT-1 study (June 2020 to January 2021), for whom 26 symptoms were assayed and the results of a PCR test were available. Adopting a variable selection approach, we sought to determine the best combination of symptoms jointly and complementarily predictive of PCR positivity and investigated whether these symptoms were the same between individuals infected by the wild-type virus and those infected by the B.1.1.7 variant. We identified 7 symptoms that were jointly predictive of PCR positivity and appeared to vary only marginally across age groups: loss or change of sense of smell, loss or change of sense of taste, fever, new persistent cough, chills, appetite loss, and muscle aches. These symptoms were also predictive of the B.1.1.7 infection, together with sore throat (to a lesser extent). What do these findings mean? Taken together, these 7 symptoms can improve the detection of COVID-19 infection in the community. Using this sparse set of symptoms for test allocation would increase the number of tests performed (up to 30%–40% of symptomatic individuals being tested) but would enable up to 75% of symptomatic cases to be detected. This set of 7 symptoms is also predictive of B.1.1.7 infection and performs similarly across age groups. Its use would maximize the case detection rate in the community and would be particularly relevant in situations where test capacity is limited.

BackgroundLateral flow immunoassays (LFIAs) have the potential to deliver affordable, large scale antibody testing and provide rapid results without the support of central laboratories. As part of the development of the REACT programme extensive evaluation of LFIA performance was undertaken with individuals following natural infection. Here we assess the performance of the selected LFIA to detect antibody responses in individuals who have received at least one dose of SARS-CoV-2 vaccine.MethodsThis is a prospective diagnostic accuracy study.SettingSampling was carried out at renal outpatient clinic and healthcare worker testing sites at Imperial College London NHS Trust. Laboratory analyses were performed across Imperial College London sites and university facilities.ParticipantsTwo cohorts of patients were recruited; the first was a cohort of 108 renal transplant patients attending clinic following SARS-CoV-2 vaccine booster, the second cohort comprised 40 healthcare workers attending for first SARS-CoV-2 vaccination, and 21 day follow up. A total of 186 paired samples were collected.InterventionsDuring the participants visit, capillary blood samples were analysed on LFIA device, while paired venous sampling was sent for serological assessment of antibodies to the spike protein (anti-S) antibodies. Anti-S IgG were detected using the Abbott Architect SARS-CoV-2 IgG Quant II CMIA.Main outcome measuresThe accuracy of Fortress LFIA in detecting IgG antibodies to SARS-CoV-2 compared to anti-spike protein detection on Abbott Assay.ResultsUsing the threshold value for positivity on serological testing of ≥7.10 BAU/ml, the overall performance of the test produces an estimate of sensitivity of 91.94% (95% CI 85.67% to 96.06%) and specificity of 93.55% (95% CI 84.30% to 98.21%) using the Abbott assay as reference standard.ConclusionsFortress LFIA performs well in the detection of antibody responses for intended purpose of population level surveys, but does not meet criteria for individual testing.

Background: SARS-CoV-2 infections have been reported in all age groups including infants, children, and adolescents. However, the role of children in the COVID-19 pandemic is still uncertain. This systematic review of early studies synthesises evidence on the susceptibility of children to SARS-CoV-2 infection, the severity and clinical outcomes in children with SARS-CoV-2 infection, and the transmissibility of SARS-CoV-2 by children in the early phases of the COVID-19 pandemic. Methods and findings: A systematic literature review was conducted in PubMed. Reviewers extracted data from relevant, peer-reviewed studies published up to July 4th 2020 during the first wave of the SARS-CoV-2 outbreak using a standardised form and assessed quality using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. For studies included in the meta-analysis, we used a random effects model to calculate pooled estimates of the proportion of children considered asymptomatic or in a severe or critical state. We identified 2,775 potential studies of which 128 studies met our inclusion criteria; data were extracted from 99, which were then quality assessed. Finally, 29 studies were considered for the meta-analysis that included information of symptoms and/or severity, these were further assessed based on patient recruitment. Our pooled estimate of the proportion of test positive children who were asymptomatic was 21.1% (95% CI: 14.0 - 28.1%), based on 13 included studies, and the proportion of children with severe or critical symptoms was 3.8% (95% CI: 1.5 - 6.0%), based on 14 included studies. We did not identify any studies designed to assess transmissibility in children and found that susceptibility to infection in children was highly variable across studies. Conclusions: Children’s susceptibility to infection and onward transmissibility relative to adults is still unclear and varied widely between studies. However, it is evident that most children experience clinically mild disease or remain asymptomatically infected. More comprehensive contact-tracing studies combined with serosurveys are needed to quantify children’s transmissibility relative to adults. With children back in schools, testing regimes and study protocols that will allow us to better understand the role of children in this pandemic are critical.

SummaryBackgroundLong COVID, describing the long-term sequelae after SARS-CoV-2 infection, remains a poorly defined syndrome. There is uncertainty about its predisposing factors and the extent of the resultant public health burden, with estimates of prevalence and duration varying widely.MethodsWithin rounds 3–5 of the REACT-2 study, 508,707 people in the community in England were asked about a prior history of COVID-19 and the presence and duration of 29 different symptoms. We used uni-and multivariable models to identify predictors of persistence of symptoms (12 weeks or more). We estimated the prevalence of symptom persistence at 12 weeks, and used unsupervised learning to cluster individuals by symptoms experienced.FindingsAmong the 508,707 participants, the weighted prevalence of self-reported COVID-19 was 19.2% (95% CI: 19.1,19.3). 37.7% of 76,155 symptomatic people post COVID-19 experienced at least one symptom, while 14.8% experienced three or more symptoms, lasting 12 weeks or more. This gives a weighted population prevalence of persistent symptoms of 5.75% (5.68, 5.81) for one and 2.22% (2.1, 2.26) for three or more symptoms. Almost a third of people (8,771/28,713 [30.5%]) with at least one symptom lasting 12 weeks or more reported having had severe COVID-19 symptoms (“significant effect on my daily life”) at the time of their illness, giving a weighted prevalence overall for this group of 1.72% (1.69,1.76). The prevalence of persistent symptoms was higher in women than men (OR: 1.51 [1.46,1.55]) and, conditional on reporting symptoms, risk of persistent symptoms increased linearly with age by 3.5 percentage points per decade of life. Obesity, smoking or vaping, hospitalisation, and deprivation were also associated with a higher probability of persistent symptoms, while Asian ethnicity was associated with a lower probability. Two stable clusters were identified based on symptoms that persisted for 12 weeks or more: in the largest cluster, tiredness predominated, while in the second there was a high prevalence of respiratory and related symptoms.InterpretationA substantial proportion of people with symptomatic COVID-19 go on to have persistent symptoms for 12 weeks or more, which is age-dependent. Clinicians need to be aware of the differing manifestations of Long COVID which may require tailored therapeutic approaches. Managing the long-term sequelae of SARS-CoV-2 infection in the population will remain a major challenge for health services in the next stage of the pandemic.FundingThe study was funded by the Department of Health and Social Care in England.Research in contextEvidence before this studyRecent systematic reviews have documented the wide range of symptoms and reported prevalence of persistent symptoms following COVID-19. A dynamic review of Long COVID studies (NIHR Evidence) in March 2021 summarised the literature on the prevalence of persistent symptoms after acute COVID19, and reported that most studies (14) were of hospitalised patients, with higher prevalence of persistent symptoms compared with two community-based studies. There was limited evidence from community studies beyond 12 weeks. Another systematic review reported a median of over 70% of people with symptoms lasting at least 60 days. A review of risk factors for Long COVID found consistent evidence for an increased risk amongst women and those with high body mass index (BMI) but inconsistent findings on the role of age and little evidence concerning risks among different socioeconomic or ethnic groups which are often not well captured in routine healthcare records. Long COVID is increasingly recognised as heterogenous, likely underpinned by differing biological mechanisms, but there is not yet consensus on defining subtypes of the condition.Added value of this studyThis community-based study of over half a million people was designed to be representative of the adult population of England. A random sample of adults ages 18 years and above registered with a GP were invited irrespective of previous access to services for COVID-19, providing an estimate of population prevalence that was representative of the whole population. The findings show substantial declines in symptom prevalence over the first 12 weeks following Covid-19, reported by nearly one fifth of respondents, of whom over a third remained symptomatic at 12 weeks and beyond, with little evidence for decline thereafter.Risk factors identified for persistent symptoms (12 weeks or more) suggestive of Long COVID confirm some previous findings - an increased risk in women, obese and overweight individuals and those hospitalised for COVID-19, with strong evidence for an increasing risk with age. Additional evidence was found for an increased risk in those with lower income, smoking or vaping and healthcare or care home workers. A lower risk was found in those of Asian ethnicity.Clustering identified two distinct groups of individuals with different symptom profiles at 12 weeks, highlighting the heterogeneity of clinical presentation. The smaller cluster had higher prevalence of respiratory and related symptoms, while for those in the larger cluster tiredness was the dominant symptom, with lower prevalence of organ-specific symptoms.Implications of available evidenceThere is a high prevalence of persistent symptoms beyond 12 weeks after acute COVID-19, with little evidence of decline thereafter. This highlights the needs for greater support for patients, both through specialised services and, for those from low-income settings, financial support. The understanding that there are distinct clusters of persistent symptoms, the most common of which is dominated by fatigue, is important for the recognition and clinical management of the condition outside of specialised services.

Influenza incidence forecasting is used to facilitate better health system planning and could potentially be used to allow at-risk individuals to modify their behavior during a severe seasonal influenza epidemic or a novel respiratory pandemic. For example, the US Centers for Disease Control and Prevention (CDC) runs an annual competition to forecast influenza-like illness (ILI) at the regional and national levels in the US, based on a standard discretized incidence scale. Here, we use a suite of forecasting models to analyze type-specific incidence at the smaller spatial scale of clusters of nearby counties. We used data from point-of-care (POC) diagnostic machines over three seasons, in 10 clusters, capturing: 57 counties; 1,061,891 total specimens; and 173,909 specimens positive for Influenza A. Total specimens were closely correlated with comparable CDC ILI data. Mechanistic models were substantially more accurate when forecasting influenza A positive POC data than total specimen POC data, especially at longer lead times. Also, models that fit subpopulations of the cluster (individual counties) separately were better able to forecast clusters than were models that directly fit to aggregated cluster data. Public health authorities may wish to consider developing forecasting pipelines for type-specific POC data in addition to ILI data. Simple mechanistic models will likely improve forecast accuracy when applied at small spatial scales to pathogen-specific data before being scaled to larger geographical units and broader syndromic data. Highly local forecasts may enable new public health messaging to encourage at-risk individuals to temporarily reduce their social mixing during seasonal peaks and guide public health intervention policy during potentially severe novel influenza pandemics., Author summary Forecasting influenza is a public health priority because it allows better planning by both policy makers and healthcare facilities. Most seasonal influenza forecasting is currently undertaken for large geographical areas and is based on the number of people who have the signs and symptoms of influenza. Different types of models can provide roughly equivalent forecasts for these data: models that use the opinion of experts, statistical models, and models that reflect the underlying biology. Newly developed data streams are resolving ever smaller spatial scales, but the impacts of coupling and smaller resolution on type-specific forecasting have not been well established. In addition to the use of local point-of-care type-specific influenza data, we assess the effects of county-to-county coupling and specific humidity on forecast outcomes. Here, we show that if the data are available for smaller geographical areas and are from actual tests for influenza, they can be forecasted accurately by models that represent the underlying biological mechanisms. Further, we add to growing evidence that mechanistic models perform better on type-specific data than they do on symptom-based data, which can be triggered by a number of respiratory viruses and/or influenza types.

Background Seroprevalence studies are essential to understand the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Various technologies, including laboratory assays and point-of-care self-tests, are available for antibody testing. The interpretation of seroprevalence studies requires comparative data on the performance of antibody tests. Methods In June 2020, current and former members of the United Kingdom police forces and fire service performed a self-test lateral flow immunoassay (LFIA), had a nurse-performed LFIA, and provided a venous blood sample for enzyme-linked immunosorbent assay (ELISA). We present the prevalence of antibodies to SARS-CoV-2 and the acceptability and usability of self-test LFIAs, and we determine the sensitivity and specificity of LFIAs compared with laboratory ELISA. Results In this cohort of 5189 current and former members of the police service and 263 members of the fire service, 7.4% (396 of 5348; 95% confidence interval [CI], 6.7–8.1) were antibody positive. Seroprevalence was 8.9% (95% CI, 6.9–11.4) in those under 40 years, 11.5% (95% CI, 8.8–15.0) in those of nonwhite ethnicity, and 7.8% (95% CI, 7.1–8.7) in those currently working. Self-test LFIA had an acceptability of 97.7% and a usability of 90.0%. There was substantial agreement between within-participant LFIA results (kappa 0.80; 95% CI, 0.77–0.83). The LFIAs had a similar performance: compared with ELISA, sensitivity was 82.1% (95% CI, 77.7–86.0) self-test and 76.4% (95% CI, 71.9–80.5) nurse-performed with specificity of 97.8% (95% CI, 97.3–98.2) and 98.5% (95% CI, 98.1–98.8), respectively. Conclusions A greater proportion of this nonhealthcare key worker cohort showed evidence of previous infection with SARS-CoV-2 than the general population at 6.0% (95% CI, 5.8–6.1) after the first wave in England. The high acceptability and usability reported by participants and similar performance of self-test and nurse-performed LFIAs indicate that the self-test LFIA is fit for purpose for home testing in occupational and community prevalence studies.

BackgroundSeroprevalence studies in key worker populations are essential to understand the epidemiology of SARS-CoV-2. Various technologies, including laboratory assays and point-of-care self-tests, are available for antibody testing. The interpretation of seroprevalence studies requires comparative data on the performance of antibody tests.MethodsIn June 2020, current and former members of the UK Police forces and Fire service performed a self-test lateral flow immunoassay (LFIA) and provided a saliva sample, nasopharyngeal swab, venous blood samples for Abbott ELISA and had a nurse performed LFIA. We present the prevalence of PCR positivity and antibodies to SARS-CoV-2 in this cohort following the first wave of infection in England; the acceptability and usability of self-test LFIAs (defined as use of the LFIA kit and provision of a valid result, respectively); and determine the sensitivity and specificity of LFIAs compared to laboratory ELISAs.ResultsIn this cohort of non-healthcare key workers, 7.4% (396/5,348; 95% CI, 6.7-8.1) were antibody positive. Seroprevalence was 8.9% (6.9-11.4) in those under 40 years, 11.5% (8.8-15.0) in those of non-white British ethnicity and 7.8% (7.1-8.7) in those currently working. The self-test LFIA had an acceptability of 97.7% and a usability of 90.0%. There was substantial agreement between within-participant LFIA results (kappa 0.80; 0.77-0.83). The LFIAs (self-test and nurse-performed) had a similar performance: compared to ELISA, sensitivity was 82.1% (77.7-86.0) self-test and 76.4% (71.9-80.5) nurse-performed with specificity of 97.8% (97.3-98.2) and 98.5% (98.1-98.8) respectively.ConclusionA greater proportion of the non-healthcare key worker cohort showed evidence of previous infection with SARS-CoV-2 than the general population at 6.0% (5.8-6.1) following the first wave in England. The high acceptability and usability reported by participants and the similar performance of self-test and nurse-performed LFIAs indicate that the self-test LFIA is fit for purpose for home-testing in occupational and community prevalence studies.

Community virus surveillance Even highly effective vaccines will not save us from the need to monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) activity, perhaps for years to come. Public health institutions will need early warning of any uptick in cases to prepare and deploy interventions as required. Riley et al. developed a community-wide program that was designed to detect resurgence at low prevalence and has been used to track SARS-CoV-2 virus across England. In the four rounds of sampling from May to September 2020, almost 600,000 people representative of all communities were monitored. The results revealed the greatest prevalence among 18- to 24-year-olds, with increasing incidence among older age groups and elevated odds of infection among some communities. This testing approach offers a model for the type of real-time, country-wide population-based surveillance work that needs to be conducted to monitor SARS-CoV-2. Science, abf0874, this issue p. 990, Representative community antigen sampling can improve situational awareness and help evaluate interventions at low SARS-CoV-2 prevalence., Surveillance of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has mainly relied on case reporting, which is biased by health service performance, test availability, and test-seeking behaviors. We report a community-wide national representative surveillance program in England based on self-administered swab results from ~594,000 individuals tested for SARS-CoV-2, regardless of symptoms, between May and the beginning of September 2020. The epidemic declined between May and July 2020 but then increased gradually from mid-August, accelerating into early September 2020 at the start of the second wave. When compared with cases detected through routine surveillance, we report here a longer period of decline and a younger age distribution. Representative community sampling for SARS-CoV-2 can substantially improve situational awareness and feed into the public health response even at low prevalence.

Background COVID-19 has plagued the globe, with multiple SARS-CoV-2 clusters hinting at its evolving epidemiology. Since the disease course is governed by important epidemiological parameters, including containment delays (time between symptom onset and mandatory isolation) and serial intervals (time between symptom onsets of infector-infectee pairs), understanding their temporal changes helps to guide interventions. Objective This study aims to characterize the epidemiology of the first two epidemic waves of COVID-19 in Hong Kong by doing the following: (1) estimating the containment delays, serial intervals, effective reproductive number (Rt), and proportion of asymptomatic cases; (2) identifying factors associated with the temporal changes of the containment delays and serial intervals; and (3) depicting COVID-19 transmission by age assortativity and types of social settings. Methods We retrieved the official case series and the Apple mobility data of Hong Kong from January-August 2020. The empirical containment delays and serial intervals were fitted to theoretical distributions, and factors associated with their temporal changes were quantified in terms of percentage contribution (the percentage change in the predicted outcome from multivariable regression models relative to a predefined comparator). Rt was estimated with the best fitted distribution for serial intervals. Results The two epidemic waves were characterized by imported cases and clusters of local cases, respectively. Rt peaked at 2.39 (wave 1) and 3.04 (wave 2). The proportion of asymptomatic cases decreased from 34.9% (0-9 years) to 12.9% (≥80 years). Log-normal distribution best fitted the 1574 containment delays (mean 5.18 [SD 3.04] days) and the 558 serial intervals (17 negative; mean 4.74 [SD 4.24] days). Containment delays decreased with involvement in a cluster (percentage contribution: 10.08%-20.73%) and case detection in the public health care sector (percentage contribution: 27.56%, 95% CI 22.52%-32.33%). Serial intervals decreased over time (6.70 days in wave 1 versus 4.35 days in wave 2) and with tertiary transmission or beyond (percentage contribution: –50.75% to –17.31%), but were lengthened by mobility (percentage contribution: 0.83%). Transmission within the same age band was high (18.1%). Households (69.9%) and social settings (20.3%) were where transmission commonly occurred. Conclusions First, the factors associated with reduced containment delays suggested government-enacted interventions were useful for achieving outbreak control and should be further encouraged. Second, the shorter serial intervals associated with the composite mobility index calls for empirical surveys to disentangle the role of different contact dimensions in disease transmission. Third, the presymptomatic transmission and asymptomatic cases underscore the importance of remaining vigilant about COVID-19. Fourth, the time-varying epidemiological parameters suggest the need to incorporate their temporal variations when depicting the epidemic trajectory. Fifth, the high proportion of transmission events occurring within the same age group supports the ban on gatherings outside of households, and underscores the need for residence-centered preventive measures.

Objective: Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) is an emerging global public health threat. In response to a highlighted strategic priority of the World Health Organization Global Action Plan on Antimicrobial Resistance, to “strengthen the knowledge and evidence base through surveillance and research”, we synthesized published articles to estimate CA-MRSA carriage prevalence in the Asia-Pacific region. Methods: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO CRD:42017067399). We searched MEDLINE, EMBASE, and PubMed for articles published from 1 January 2000 to 19 May 2017, which reported CA-MRSA carriage (defined as either colonization or infection) in Asia-Pacific region from 2000 to 2016. Studies were stratified according to settings (community or hospital where CA-MRSA was isolated) and study populations (general public or subpopulations with specified characteristics). Ranges of CA-MRSA carriage prevalence were reported for study groups. Results: In total, 152 studies were identified. Large diversity was observed among studies in most study groups. In community-level studies, the CA-MRSA carriage prevalence among the general public ranged from 0% to 23.5%, whereas that ranged from 0.7% to 10.4% in hospital settings. From community-level studies, countries with the highest prevalence were India (16.5%–23.5%), followed by Vietnam (7.9%) and Taiwan (3.5%–3.8%). Children aged ≤6 (range: 0.5%–40.3%) and household members of CA-MRSA carriers (range: 13.0%–26.4%) are subgroups without specific health conditions but with much higher CA-MRSA carriage when compared to the general population. Conclusion: Our CA-MRSA prevalence estimates serve as the baseline for future national and international surveillance. The ranges of prevalence and characteristics associated with CA-MRSA carriage can inform health authorities to formulate infection control policies for high-risk subgroups. Future studies should explore the heterogeneities in CA-MRSA carriage prevalence among subgroups and countries to clarify the predominant transmission mechanisms in Asia-Pacific and other regions.

BackgroundEngland will start to exit its third national lockdown in response to the COVID-19 pandemic on 8th March 2021, with safe effective vaccines being rolled out rapidly against a background of emerging transmissible and immunologically novel variants of SARS-CoV-2. A subsequent increase in community prevalence of infection could delay further relaxation of lockdown if vaccine uptake and efficacy are not sufficiently high to prevent increased pressure on healthcare services.MethodsThe PCR self-swab arm of the REal-time Assessment of Community Transmission Study (REACT-1) estimates community prevalence of SARS-CoV-2 infection in England based on random cross-sections of the population ages five and over. Here, we present results from the complete round 9 of REACT-1 comprising round 9a in which swabs were collected from 4th to 12th February 2021 and round 9b from 13th to 23rd February 2021. We also compare the results of REACT-1 round 9 to round 8, in which swabs were collected mainly from 6th January to 22nd January 2021.ResultsOut of 165,456 results for round 9 overall, 689 were positive. Overall weighted prevalence of infection in the community in England was 0.49% (0.44%, 0.55%), representing a fall of over two thirds from round 8. However the rate of decline of the epidemic has slowed from 15 (13, 17) days, estimated for the period from the end of round 8 to the start of round 9, to 31 days estimated using data from round 9 alone (lower confidence limit 17 days). When comparing round 9a to 9b there were apparent falls in four regions, no apparent change in one region and apparent rises in four regions, including London where there was a suggestion of sub-regional heterogeneity in growth and decline. Smoothed prevalence maps suggest large contiguous areas of growth and decline that do not align with administrative regions.Prevalence fell by 50% or more across all age groups in round 9 compared to round 8, with prevalence (round 9) ranging from 0.21% in those aged 65 and over to 0.71% in those aged 13 to 17 years. Round 9 prevalence was highest among Pakistani participants at 2.1% compared to white participants at 0.45% and Black participants at 0.83%. There were higher adjusted odds of infection for healthcare and care home workers, for those working in public transport and those working in education, school, nursery or childcare and lower adjusted odds for those not required to work outside the home.ConclusionsCommunity prevalence of swab-positivity has declined markedly between January and February 2021 during lockdown in England, but remains high; the rate of decline has slowed in the most recent period, with a suggestion of pockets of growth. Continued adherence to social distancing and public health measures is required so that infection rates fall to much lower levels. This will help to ensure that the benefits of the vaccination roll-out programme in England are fully realised.

Objective To evaluate the performance of new lateral flow immunoassays (LFIAs) suitable for use in a national coronavirus disease 2019 (covid-19) seroprevalence programme (real time assessment of community transmission 2—React 2). Design Diagnostic accuracy study. Setting Laboratory analyses were performed in the United Kingdom at Imperial College, London and university facilities in London. Research clinics for finger prick sampling were run in two affiliated NHS trusts. Participants Sensitivity analyses were performed on sera stored from 320 previous participants in the React 2 programme with confirmed previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Specificity analyses were performed on 1000 prepandemic serum samples. 100 new participants with confirmed previous SARS-CoV-2 infection attended study clinics for finger prick testing. Interventions Laboratory sensitivity and specificity analyses were performed for seven LFIAs on a minimum of 200 serum samples from participants with confirmed SARS-CoV-2 infection and 500 prepandemic serum samples, respectively. Three LFIAs were found to have a laboratory sensitivity superior to the finger prick sensitivity of the LFIA currently used in React 2 seroprevalence studies (84%). These LFIAs were then further evaluated through finger prick testing on participants with confirmed previous SARS-CoV-2 infection: two LFIAs (Surescreen, Panbio) were evaluated in clinics in June-July 2020 and the third LFIA (AbC-19) in September 2020. A spike protein enzyme linked immunoassay and hybrid double antigen binding assay were used as laboratory reference standards. Main outcome measures The accuracy of LFIAs in detecting immunoglobulin G (IgG) antibodies to SARS-CoV-2 compared with two reference standards. Results The sensitivity and specificity of seven new LFIAs that were analysed using sera varied from 69% to 100%, and from 98.6% to 100%, respectively (compared with the two reference standards). Sensitivity on finger prick testing was 77% (95% confidence interval 61.4% to 88.2%) for Panbio, 86% (72.7% to 94.8%) for Surescreen, and 69% (53.8% to 81.3%) for AbC-19 compared with the reference standards. Sensitivity for sera from matched clinical samples performed on AbC-19 was significantly higher with serum than finger prick at 92% (80.0% to 97.7%, P=0.01). Antibody titres varied considerably among cohorts. The numbers of positive samples identified by finger prick in the lowest antibody titre quarter varied among LFIAs. Conclusions One new LFIA was identified with clinical performance suitable for potential inclusion in seroprevalence studies. However, none of the LFIAs tested had clearly superior performance to the LFIA currently used in React 2 seroprevalence surveys, and none showed sufficient sensitivity and specificity to be considered for routine clinical use.

SummaryControl of the SARS-CoV-2 epidemic requires rapid identification and isolation of infected individuals and their contacts. Community testing in England (Pillar 2) by polymerase chain reaction (PCR) is reserved for those reporting at least one of four ‘classic’ COVID-19 symptoms (loss or change of sense of smell, loss or change of sense of taste, fever, new continuous cough).1 Detection of positive cases in the community might be improved by including additional symptoms and their combinations. We used data from the REal-time Assessment of Community Transmission-1 (REACT-1) study to investigate symptom profiles for PCR positivity at different ages. Among rounds 2–7 (June to December 2020), an age-stratified, variable selection approach stably selected chills (all ages), headache (5–17 years), appetite loss (18–54 and 55+ years) and muscle aches (18–54 years) as jointly and positively predictive of PCR positivity together with the classic four symptoms. Between round 7 (November to December 2020) and round 8 (January 2021) when new variant B.1.1.7 predominated, only loss or change of sense of smell (more predictive in round 7) and (borderline) new persistent cough (more predictive in round 8) differed between cases. At any level of PCR testing, triage based on the symptoms identified here would result in more cases detected than the current approach.

BackgroundThe prevalence and persistence of antibodies following a peak SARS-CoV-2 infection provides insights into its spread in the community, the likelihood of reinfection and potential for some level of population immunity.MethodsPrevalence of antibody positivity in England, UK (REACT2) with three cross-sectional surveys between late June and September 2020. 365104 adults used a self-administered lateral flow immunoassay (LFIA) test for IgG. A laboratory comparison of LFIA results to neutralization activity in panel of sera was performed.ResultsThere were 17,576 positive tests over the three rounds. Antibody prevalence, adjusted for test characteristics and weighted to the adult population of England, declined from 6.0% [5.8, 6.1], to 4.8% [4.7, 5.0] and 4.4% [4.3, 4.5], a fall of 26.5% [-29.0, −23.8] over the three months of the study. There was a decline between rounds 1 and 3 in all age groups, with the highest prevalence of a positive result and smallest overall decline in positivity in the youngest age group (18-24 years: −14.9% [-21.6, −8.1]), and lowest prevalence and largest decline in the oldest group (75+ years: −39.0% [-50.8, −27.2]); there was no change in antibody positivity between rounds 1 and 3 in healthcare workers (+3.45% [-5.7, +12.7]).The decline from rounds 1 to 3 was largest in those who did not report a history of COVID-19, (−64.0% [-75.6, −52.3]), compared to −22.3% ([-27.0, −17.7]) in those with SARS-CoV-2 infection confirmed on PCR.DiscussionThese findings provide evidence of variable waning in antibody positivity over time such that, at the start of the second wave of infection in England, only 4.4% of adults had detectable IgG antibodies using an LFIA. Antibody positivity was greater in those who reported a positive PCR and lower in older people and those with asymptomatic infection. These data suggest the possibility of decreasing population immunity and increasing risk of reinfection as detectable antibodies decline in the population.

2.AbstractImportanceDevising control strategies against diseases such as COVID-19 require understanding of contextual social mixing and contact patterns. There has been no standardized multi-site social contact study conducted in workplace settings in the United States that can be used to broadly inform pandemic preparedness policy in these settings.ObjectiveThe study aimed to characterize the patterns of social contacts and mixing across workplace environments, including on-site or when teleworking.DesignThis was a cross-sectional non-probability survey that used standardized social contact diaries to collect data. Employees were requested to record their physical and non-physical contacts in a diary over two consecutive days, documented at the end of each day. Employees from each company were enrolled through email and electronic diaries sent as individual links. Data were collected from April to June 2020.SettingTwo multinational consulting companies and one university administrative department, all located in Georgia, USA.ParticipantsEmployees opted into the study by accepting the invitation on a link sent via email.Main OutcomeThe outcome was median number of contacts per person per day. This was stratified by day of data collection, age, sex, race and ethnicity.ResultsOf 3,835 employees approached, 357 (9.3%) completed the first day of contact diary of which 304 completed both days of contact diary. There was a median of 2 contacts (IQR: 1-4, range: 0-21) per respondent on both day one and two. The majority (55%) of contacts involved conversation only, occurred at home (64%), and cumulatively lasted more than 4 hours (38%). Most contacts were repeated, and within same age groups, though participants aged 30-59 years reported substantial inter-generational mixing with children.ConclusionParticipating employees in 3 surveyed workplaces reported few contacts, similar to studies from the UK and China when shelter-in-place orders were in effect during the pandemic. Many contacts were repeated which may limit the spread of infection. Future rounds are planned to assess changes in contact patterns when employees resume work in the office after the lockdown due to COVID-19 pandemic.

Background After experiencing a sharp growth in COVID-19 cases early in the pandemic, South Korea rapidly controlled transmission while implementing less stringent national social distancing measures than countries in Europe and the USA. This has led to substantial interest in their “test, trace, isolate” strategy. However, it is important to understand the epidemiological peculiarities of South Korea’s outbreak and characterise their response before attempting to emulate these measures elsewhere. Methods We systematically extracted numbers of suspected cases tested, PCR-confirmed cases, deaths, isolated confirmed cases, and numbers of confirmed cases with an identified epidemiological link from publicly available data. We estimated the time-varying reproduction number, Rt, using an established Bayesian framework, and reviewed the package of interventions implemented by South Korea using our extracted data, plus published literature and government sources. Results We estimated that after the initial rapid growth in cases, Rt dropped below one in early April before increasing to a maximum of 1.94 (95%CrI, 1.64–2.27) in May following outbreaks in Seoul Metropolitan Region. By mid-June, Rt was back below one where it remained until the end of our study (July 13th). Despite less stringent “lockdown” measures, strong social distancing measures were implemented in high-incidence areas and studies measured a considerable national decrease in movement in late February. Testing the capacity was swiftly increased, and protocols were in place to isolate suspected and confirmed cases quickly; however, we could not estimate the delay to isolation using our data. Accounting for just 10% of cases, individual case-based contact tracing picked up a relatively minor proportion of total cases, with cluster investigations accounting for 66%. Conclusions Whilst early adoption of testing and contact tracing is likely to be important for South Korea’s successful outbreak control, other factors including regional implementation of strong social distancing measures likely also contributed. The high volume of testing and the low number of deaths suggest that South Korea experienced a small epidemic relative to other countries. Caution is needed in attempting to replicate the South Korean response in populations with larger more geographically widespread epidemics where finding, testing, and isolating cases that are linked to clusters may be more difficult.

SummaryBackgroundBased on cases and deaths, transmission of SARS-CoV-2 in England peaked in late March and early April 2020 and then declined until the end of June. Since the start of July, cases have increased, while deaths have continued to decrease.MethodsWe report results from 594,000 swabs tested for SARS-CoV-2 virus obtained from a representative sample of people in England over four rounds collected regardless of symptoms, starting in May 2020 and finishing at the beginning of September 2020. Swabs for the most recent two rounds were taken between 24th July and 11th August and for round 4 between 22nd August and 7th September. We estimate weighted overall prevalence, doubling times between and within rounds and associated reproduction numbers. We obtained unweighted prevalence estimates by sub-groups: age, sex, region, ethnicity, key worker status, household size, for which we also estimated odds of infection. We identified clusters of swab-positive participants who were closer, on average, to other swab-positive participants than would be expected.FindingsOver all four rounds of the study, we found that 72% (67%, 76%) of swab-positive individuals were asymptomatic at the time of swab and in the week prior. The epidemic declined between rounds 1 and 2, and rounds 2 and 3. However, the epidemic was increasing between rounds 3 and 4, with a doubling time of 17 (13, 23) days corresponding to an R value of 1.3 (1.2, 1.4). When analysing round 3 alone, we found that the epidemic had started to grow again with 93% probability. Using only the most recent round 4 data, we estimated a doubling time of 7.7 (5.5, 12.7) days, corresponding to an R value of 1.7 (1.4, 2.0). Cycle threshold values were lower (viral loads were higher) for rounds 1 and 4 than they were for rounds 2 and 3. In round 4, we observed the highest prevalence in participants aged 18 to 24 years at 0.25% (0.16%, 0.41%), increasing from 0.08% (0.04%, 0.18%) in round 3. We observed the lowest prevalence in those aged 65 and older at 0.04% (0.02%, 0.06%) which was stable compared with round 3. Participants of Asian ethnicity had elevated odds of infection. We identified clusters in and around London, transient clusters in the Midlands, and an expanding area of clustering in the North West and more recently in Yorkshire and the Humber.InterpretationAlthough low levels of transmission persisted in England through to mid-summer 2020, the prevalence of SARS-CoV-2 is now increasing. We found evidence of accelerating transmission at the end of August and beginning of September. Representative community antigen sampling can increase situational awareness and help improve public health decision making even at low prevalence.

Highlight We estimated SARS-CoV-2 infection prevalence in cohorts of repatriated citizens from Wuhan to be 0.44% (95% CI: 0.19%–1.03%). Although not representative of the wider population we believe these estimates are helpful in providing a conservative estimate of infection prevalence in Wuhan City, China, in the absence of large-scale population testing early in the epidemic.

BackgroundAccurate antibody tests are essential to monitor the SARS-CoV-2 pandemic. Lateral flow immunoassays (LFIAs) can deliver testing at scale. However, reported performance varies, and sensitivity analyses have generally been conducted on serum from hospitalised patients. For use in community testing, evaluation of finger-prick self-tests, in non-hospitalised individuals, is required.MethodsSensitivity analysis was conducted on 276 non-hospitalised participants. All had tested positive for SARS-CoV-2 by reverse transcription PCR and were ≥21 days from symptom onset. In phase I, we evaluated five LFIAs in clinic (with finger prick) and laboratory (with blood and sera) in comparison to (1) PCR-confirmed infection and (2) presence of SARS-CoV-2 antibodies on two ‘in-house’ ELISAs. Specificity analysis was performed on 500 prepandemic sera. In phase II, six additional LFIAs were assessed with serum.Findings95% (95% CI 92.2% to 97.3%) of the infected cohort had detectable antibodies on at least one ELISA. LFIA sensitivity was variable, but significantly inferior to ELISA in 8 out of 11 assessed. Of LFIAs assessed in both clinic and laboratory, finger-prick self-test sensitivity varied from 21% to 92% versus PCR-confirmed cases and from 22% to 96% versus composite ELISA positives. Concordance between finger-prick and serum testing was at best moderate (kappa 0.56) and, at worst, slight (kappa 0.13). All LFIAs had high specificity (97.2%–99.8%).InterpretationLFIA sensitivity and sample concordance is variable, highlighting the importance of evaluations in setting of intended use. This rigorous approach to LFIA evaluation identified a test with high specificity (98.6% (95%CI 97.1% to 99.4%)), moderate sensitivity (84.4% with finger prick (95% CI 70.5% to 93.5%)) and moderate concordance, suitable for seroprevalence surveys.

BackgroundEngland has experienced one of the highest rates of confirmed COVID-19 mortality in the world. SARS-CoV-2 virus has circulated in hospitals, care homes and the community since January 2020. Our current epidemiological knowledge is largely informed by clinical cases with far less understanding of community transmission.MethodsThe REal-time Assessment of Community Transmission (REACT) study is a nationally representative prevalence survey of SARS-CoV-2 virus swab-positivity in the community in England. We recruited participants regardless of symptom status.ResultsWe found 159 positives from 120,610 swabs giving an average prevalence of 0.13% (95% CI: 0.11%,0.15%) from 1st May to 1st June 2020. We showed decreasing prevalence with a halving time of 8.6 (6.2, 13.6) days, implying an overall reproduction number R of 0.57 (0.45, 0.72). Adults aged 18 to 24 yrs had the highest swab-positivity rates, while those >64 yrs had the lowest. Of the 126 participants who tested positive with known symptom status in the week prior to their swab, 39 reported symptoms while 87 did not, giving an estimate that 69% (61%,76%) of people were symptom-free for the 7 days prior testing positive in our community sample. Symptoms strongly associated with swab-positivity were: nausea and/or vomiting, diarrhoea, blocked nose, loss of smell, loss of taste, headache, chills and severe fatigue. Recent contact with a known COVID-19 case was associated with odds of 24 (16, 38) for swab-positivity. Compared with non-key workers, odds of swab-positivity were 7.7 (2.4, 25) among care home (long-term care facilities) workers and 5.2 (2.9, 9.3) among health care workers. However, some of the excess risk associated with key worker status was explained by recent contact with COVID-19 cases. We found no strong evidence for geographical variability in positive swab results.ConclusionOur results provide a reliable baseline against which the impact of subsequent relaxation of lockdown can be assessed to inform future public health efforts to control transmission.

Background This study assesses acceptability and usability of home-based self-testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies using lateral flow immunoassays (LFIA). Methods We carried out public involvement and pilot testing in 315 volunteers to improve usability. Feedback was obtained through online discussions, questionnaires, observations, and interviews of people who tried the test at home. This informed the design of a nationally representative survey of adults in England using two LFIAs (LFIA1 and LFIA2) which were sent to 10 600 and 3800 participants, respectively, who provided further feedback. Results Public involvement and pilot testing showed high levels of acceptability, but limitations with the usability of kits. Most people reported completing the test; however, they identified difficulties with practical aspects of the kit, particularly the lancet and pipette, a need for clearer instructions and more guidance on interpretation of results. In the national study, 99.3% (8693/8754) of LFIA1 and 98.4% (2911/2957) of LFIA2 respondents attempted the test and 97.5% and 97.8% of respondents completed it, respectively. Most found the instructions easy to understand, but some reported difficulties using the pipette (LFIA1: 17.7%) and applying the blood drop to the cassette (LFIA2: 31.3%). Most respondents obtained a valid result (LFIA1: 91.5%; LFIA2: 94.4%). Overall there was substantial concordance between participant and clinician interpreted results (kappa: LFIA1 0.72; LFIA2 0.89). Conclusions Impactful public involvement is feasible in a rapid response setting. Home self-testing with LFIAs can be used with a high degree of acceptability and usability by adults, making them a good option for use in seroprevalence surveys.

Timely and accurate knowledge of Dengue incidence is of value to public health professionals because it helps to enable the precise communication of risk, improved allocation of resources to potential interventions, and improved planning for the provision of clinical care of severe cases. Therefore, many national public health organizations make local Dengue incidence data publicly available for individuals and organizations to use to manage current risk. The availability of these data has also resulted in active research into the forecasting of Dengue incidence as a way to increase the public health value of incidence data. Here, we robustly assess time-series-based forecasting approaches against a null model (historical average incidence) for the forecasting of incidence up to four months ahead. We used publicly available data from multiple countries: Brazil, Mexico, Singapore, Sri Lanka, and Thailand; and found that our time series methods are more accurate than the null model across all populations, especially for 1-and 2-month ahead forecasts. We tested whether the inclusion of climatic data improved forecast accuracy and found only modest, if any improvements. We also tested whether national timeseries forecasts are more accurate if made from aggregate sub-national forecasts, and found mixed results. We used our forecasting results to illustrate the high value of increased reporting speed. This framework and test data are available as an R package. The non-mechanistic approaches described here motivates further research into the use of disease-dynamic models to increase the accuracy of medium-term Dengue forecasting across multiple populations.Author summaryDengue is a mosquito-borne disease caused by the Dengue virus. Since the Second World War it has evolved into a global problem, securing a foothold in more than 100 countries. Each year, hundreds of millions of people become infected, and upwards of 10,000 die from the disease. Thus, being able to accurately forecast the number of cases likely to emerge in particular locations is vital for public health professionals to be able to develop appropriate plans. In this study, we have refined a technique that allows us to forecast the number of cases of Dengue in a particular location, up to four months in advance. We test the approach using state-level and national-level data from Brazil, Mexico, Singapore, Sri Lanka, and Thailand. We found that the model can generally make useful forecasts, particularly on a two-month horizon. We tested whether information about climatic conditions improved the forecast, and found only modest improvements to the forecast. Our results highlight the need for both timely and accurate reports. We also anticipate that this approach may be more generally useful to the scientific community; thus, we are releasing a framework, which will allow interested parties to replicate our work, as well as apply it to other sources of Dengue data, as well as other infectious diseases in general.

Background: As of August 2021, every region of the world has been affected by the COVID-19 pandemic, with more than 196,000,000 cases worldwide. Methods: We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries. Results: Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that up to 70% (95% CI: 54% - 80%) of imported cases could remain undetected relative to the sensitivity of surveillance in Singapore. The percentage of undetected imported cases rises to 75% (95% CI 66% - 82%) when comparing to the surveillance sensitivity in multiple countries. Conclusions: Our analysis shows that a large number of COVID-19 cases remain undetected across the world. These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.

Health planners from global to local levels must anticipate year‐to‐year and week‐to‐week variation in seasonal influenza activity when planning for and responding to epidemics to mitigate their impact. To help with this, countries routinely collect incidence of mild and severe respiratory illness and virologic data on circulating subtypes and use these data for situational awareness, burden of disease estimates and severity assessments. Advanced analytics and modelling are increasingly used to aid planning and response activities by describing key features of influenza activity for a given location and generating forecasts that can be translated to useful actions such as enhanced risk communications, and informing clinical supply chains. Here, we describe the formation of the Influenza Incidence Analytics Group (IIAG), a coordinated global effort to apply advanced analytics and modelling to public influenza data, both epidemiological and virologic, in real‐time and thus provide additional insights to countries who provide routine surveillance data to WHO. Our objectives are to systematically increase the value of data to health planners by applying advanced analytics and forecasting and for results to be immediately reproducible and deployable using an open repository of data and code. We expect the resources we develop and the associated community to provide an attractive option for the open analysis of key epidemiological data during seasonal epidemics and the early stages of an influenza pandemic.

Directly measuring evidence of influenza infections is difficult, especially in low-surveillance settings such as sub-Saharan Africa. Using a Bayesian model, we estimated unobserved infection times and underlying antibody responses to influenza A/H3N2, using cross-sectional serum antibody responses to 4 strains in children aged 24–60 months. Among the 242 individuals, we estimated a variable seasonal attack rate and found that most children had ≥1 infection before 2 years of age. Our results are consistent with previously published high attack rates in children. The modeling approach highlights how cross-sectional serological data can be used to estimate epidemiological dynamics.

Aims Tafamidis is an effective treatment for transthyretin amyloid cardiomyopathy (ATTR-CM) in the Tafamidis in Transthyretin Cardiomyopathy Clinical Trial (ATTR-ACT). While ATTR-ACT was not designed for a dose-specific assessment, further analysis from ATTR-ACT and its long-term extension study (LTE) can guide determination of the optimal dose. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methods and results In ATTR-ACT, patients were randomized (2:1:2) to tafamidis 80 mg, 20mg, or placebo for 30months. Patients completing ATTR-ACT could enrol in the LTE (with placebo-treated patients randomized to tafamidis 80 or 20 mg; 2:1) and all patients were subsequently switched to high-dose tafamidis. All-cause mortality was assessed in ATTR-ACT combined with the LTE (median follow-up 51 months). In ATTR-ACT, the combination of all-cause mortality and cardiovascular-related hospitalizations over 30 months was significantly reduced with tafamidis 80mg (P = 0.0030) and 20mg (P = 0.0048) vs. placebo. All-cause mortality vs. placebo was reduced with tafamidis 80mg [Cox hazards model (95% confidence interval (CI): 0.690 (0.487–0.979), P = 0.0378] and 20mg [0.715 (0.450–1.137), P = 0.1564]. The mean (standard error) change in N-terminal pro-B-type natriuretic peptide from baseline to Month 30 was −1170.51 (587.31) (P = 0.0468) with tafamidis 80 vs. 20 mg. In ATTR-ACT combined with the LTE there was a significantly greater survival benefit with tafamidis 80 vs. 20 mg [0.700 (0.501–0.979), P = 0.0374]. Incidence of adverse events in both tafamidis doses were comparable to placebo. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion Tafamidis, both 80 and 20mg, effectively reduced mortality and cardiovascular-related hospitalizations in patients with ATTR-CM. The longer-term survival data and the lack of dose-related safety concerns support tafamidis 80mg as the optimal dose. Clinical Trial Registration: ClinicalTrials.gov NCT01994889; NCT02791230 post-print 369 KB

Background: England, UK has one of the highest rates of confirmed COVID-19 mortality globally. Until recently, testing for the SARS-CoV-2 virus focused mainly on healthcare and care home settings. As such, there is far less understanding of community transmission. Protocol: The REal-time Assessment of Community Transmission (REACT) programme is a major programme of home testing for COVID-19 to track progress of the infection in the community. REACT-1 involves cross-sectional surveys of viral detection (virological swab for RT-PCR) tests in repeated samples of 100,000 to 150,000 randomly selected individuals across England. This examines how widely the virus has spread and how many people are currently infected. The age range is 5 years and above. Individuals are sampled from the England NHS patient list. REACT-2 is a series of five sub-studies towards establishing the seroprevalence of antibodies to SARS-CoV-2 in England as an indicator of historical infection. The main study (study 5) uses the same design and sampling approach as REACT-1 using a self-administered lateral flow immunoassay (LFIA) test for IgG antibodies in repeated samples of 100,000 to 200,000 adults aged 18 years and above. To inform study 5, studies 1-4 evaluate performance characteristics of SARS-CoV-2 LFIAs (study 1) and different aspects of feasibility, usability and application of LFIAs for home-based testing in different populations (studies 2-4). Ethics and dissemination: The study has ethical approval. Results are reported using STROBE guidelines and disseminated through reports to public health bodies, presentations at scientific meetings and open access publications. Conclusions: This study provides robust estimates of the prevalence of both virus (RT-PCR, REACT-1) and seroprevalence (antibody, REACT-2) in the general population in England. We also explore acceptability and usability of LFIAs for self-administered testing for SARS-CoV-2 antibody in a home-based setting, not done before at such scale in the general population.

Objectives We conducted a cross-sectional study in Hong Kong community to estimate the carriage prevalence, associated factors and genotypes of extended-spectrum beta-lactamase producing Enterobacteriaceae (ESBL-E), methicillin-resistant Staphylococcus aureus (MRSA) and carbapenemase-producing Enterobacteriaceae (CPE). Methods Seemingly healthy subjects were asked to provide nasal, handprint and stool samples from March to April 2017. Isolates were characterized by molecular methods. We used multivariable logistic regression models within a generalized estimating equation framework to identify risk factors for ESBL-E carriage. Characteristics of MRSA/CPE carriage were summarized. Results The prevalence of ESBL-E, MRSA and CPE were 52.8% (104/197), 2.5% (5/197) and 0.5% (1/197) respectively. Most ESBL-E isolates were E. coli (85.6%; 113/132). Most ESBL genes belonged to blaCTX−M-G9 (68.9%) and blaTEM (53.0%) types. Self-reported antibiotic consumption (≥2 courses) in the past six months was associated with ESBL-E carriage (adjusted odds ratio: 4.71–5.47). Conclusions Abundance of ESBL-E in the community are causes of concern, and antibiotic use is associated with its carriage. Presence of MRSA and CPE in community members without clear healthcare exposure hints on a change in their epidemiology. This study establishes a baseline to formulate infection control policies and future studies in combating antimicrobial resistance.

Infectious disease modeling has played a prominent role in recent outbreaks, yet integrating these analyses into public health decision-making has been challenging. We recommend establishing ‘outbreak science’ as an inter-disciplinary field to improve applied epidemic modeling.

Background A significant increase in microcephaly incidence was reported in Northeast Brazil at the end of 2015, which has since been attributed to an epidemic of Zika virus (ZIKV) infections earlier that year. Further incidence of congenital Zika syndrome (CZS) was expected following waves of ZIKV infection throughout Latin America; however, only modest increases in microcephaly and CZS incidence have since been observed. The quantitative relationship between ZIKV infection, gestational age and congenital outcome remains poorly understood. Methodology/Principle findings We characterised the gestational-age-varying risk of microcephaly given ZIKV infection using publicly available incidence data from multiple locations in Brazil and Colombia. We found that the relative timings and shapes of ZIKV infection and microcephaly incidence curves suggested different gestational risk profiles for different locations, varying in both the duration and magnitude of gestational risk. Data from Northeast Brazil suggested a narrow window of risk during the first trimester, whereas data from Colombia suggested persistent risk throughout pregnancy. We then used the model to estimate which combination of behavioural and reporting changes would have been sufficient to explain the absence of a second microcephaly incidence wave in Bahia, Brazil; a population for which we had two years of data. We found that a 18.9-fold increase in ZIKV infection reporting rate was consistent with observed patterns. Conclusions Our study illustrates how surveillance data may be used in principle to answer key questions in the absence of directed epidemiological studies. However, in this case, we suggest that currently available surveillance data are insufficient to accurately estimate the gestational-age-varying risk of microcephaly from ZIKV infection. The methods used here may be of use in future outbreaks and may help to inform improved surveillance and interpretation in countries yet to experience an outbreak of ZIKV infection., Author summary Zika virus (ZIKV) infection is associated with the rise of microcephaly cases observed in Northeast Brazil at the end of 2015. For women in endemic or at-risk areas, understanding how the relationship between time of infection and microcephaly risk varies through pregnancy is important in informing family planning. However, a relatively modest number of congenital Zika syndrome cases have been observed following subsequent waves of ZIKV infection, limiting our understanding of gestational risk. We used a mathematical model to quantify the shape and magnitude of the gestational-age-varying risk to a fetus. Although the risk profile should be conserved regardless of location, we estimated different profiles when using surveillance data from locations in Northeast Brazil and Colombia. Our results suggest that time-dependent reporting changes likely confound the interpretation of currently available surveillance data. Furthermore, we investigated a range of behavioural and reporting rate changes that could explain two waves of ZIKV infection in Bahia, Brazil despite only one wave of microcephaly. Plausible changes in reporting could explain these data whilst remaining consistent with the hypothesis that ZIKV infection carries a significant risk of microcephaly. Further evidence is needed to disentangle the true risk of congenital Zika syndrome from time-varying reporting changes.

We present a flexible, open source R package designed to obtain biological and epidemiological insights from serological datasets. Characterising past exposures for multi-strain pathogens poses a specific statistical challenge: observed antibody responses measured in serological assays depend on multiple unobserved prior infections that produce cross-reactive antibody responses. We provide a general modelling framework to jointly infer infection histories and describe immune responses generated by these infections using antibody titres against current and historical strains. We do this by linking latent infection dynamics with a mechanistic model of antibody kinetics that generates expected antibody titres over time. Our aim is to provide a flexible package to identify infection histories that can be applied to a range of pathogens. We present two case studies to illustrate how our model can infer key immunological parameters, such as antibody titre boosting, waning and cross-reaction, as well as latent epidemiological processes such as attack rates and age-stratified infection risk., Author summary Antibody levels can determine previous exposure to a pathogen and how likely individuals are to be infected in the future. However, antibody concentrations change over time, and some pathogens are continually evolving. In such cases, individuals may be infected and vaccinated multiple times when their pre-existing immunity fails, leading to a wide range of antibody profiles. Traditional approaches to analyse such data do not typically account for this. In addition, studies collecting antibody data may be designed differently, but are often underpinned by similar biological processes. We developed a statistical method and accompanying software package to better understand the immunology and epidemiology of these complex systems using serological data. We present two case studies to demonstrate how our software package, serosolver, can be applied to different settings: i) the epidemiology of the 2009 pandemic A/H1N1 influenza virus in Hong Kong and ii) historical patterns of A/H3N2 influenza infection in Guangzhou, China. These results demonstrate how modern analytical methods can reveal additional information from serological data that is otherwise missed using traditional approaches.

BACKGROUND: Transthyretin amyloid cardiomyopathy is caused by the deposition of transthyretin amyloid fibrils in the myocardium. The deposition occurs when wild-type or variant transthyretin becomes unstable and misfolds. Tafamidis binds to transthyretin, preventing tetramer dissociation and amyloidogenesis. METHODS: In a multicenter, international, double-blind, placebo-controlled, phase 3 trial, we randomly assigned 441 patients with transthyretin amyloid cardiomyopathy in a 2:1:2 ratio to receive 80 mg of tafamidis, 20 mg of tafamidis, or placebo for 30 months. In the primary analysis, we hierarchically assessed all-cause mortality, followed by frequency of cardiovascular-related hospitalizations according to the Finkelstein-Schoenfeld method. Key secondary end points were the change from baseline to month 30 for the 6-minute walk test and the score on the Kansas City Cardiomyopathy Questionnaire-Overall Summary (KCCQ-OS), in which higher scores indicate better health status. RESULTS: In the primary analysis, all-cause mortality and rates of cardiovascular-related hospitalizations were lower among the 264 patients who received tafamidis than among the 177 patients who received placebo (P

Transthyretin amyloidosis is a rare, life-threatening disease resulting from aggregation and deposition of transthyretin amyloid fibrils in various tissues. There are 2 predominate phenotypic presentations of the disease: transthyretin familial amyloid polyneuropathy, which primarily affects the peripheral nerves, and transthyretin cardiomyopathy (TTR-CM), which primarily affects the heart. However, there is a wide overlap with symptoms at presentation and disease course being highly variable and influenced by the underlying transthyretin mutation, age of the affected individual, sex, and geographic location. Treatment of transthyretin amyloidosis is typically focused on symptom management. Although tafamidis has been shown to delay neurologic progression of transthyretin familial amyloid polyneuropathy, there are no approved pharmacologic therapies shown to improve survival in TTR-CM. The natural history of TTR-CM is poorly characterized, which presents difficulties for the design of large-scale trials for new treatments. This review provides a brief overview of TTR-CM and the challenges of identifying clinically meaningful end points and study parameters to determine the efficacy of treatments for rare diseases. The design and rationale behind the ongoing phase 3 ATTR-ACT study (Tafamidis in Transthyretin Cardiomyopathy Clinical Trial), an international, multicenter, double-blind, placebo-controlled, randomized clinical trial, is also outlined. The ATTR-ACT study will provide important insight into the efficacy and safety of tafamidis for the treatment of TTR-CM. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT01994889.

Background The ongoing West African Ebola epidemic began in December 2013 in Guinea, probably from a single zoonotic introduction. As a result of ineffective initial control efforts, an Ebola outbreak of unprecedented scale emerged. As of 4 May 2015, it had resulted in more than 19,000 probable and confirmed Ebola cases, mainly in Guinea (3,529), Liberia (5,343), and Sierra Leone (10,746). Here, we present analyses of data collected during the outbreak identifying drivers of transmission and highlighting areas where control could be improved. Methods and Findings Over 19,000 confirmed and probable Ebola cases were reported in West Africa by 4 May 2015. Individuals with confirmed or probable Ebola (“cases”) were asked if they had exposure to other potential Ebola cases (“potential source contacts”) in a funeral or non-funeral context prior to becoming ill. We performed retrospective analyses of a case line-list, collated from national databases of case investigation forms that have been reported to WHO. These analyses were initially performed to assist WHO’s response during the epidemic, and have been updated for publication. We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. The proportion of cases reporting a funeral exposure decreased over time. We found a positive correlation (r = 0.35, p < 0.001) between this proportion in a given district for a given month and the within-district transmission intensity, quantified by the estimated reproduction number (R). We also found a negative correlation (r = −0.37, p < 0.001) between R and the district proportion of hospitalised cases admitted within ≤4 days of symptom onset. These two proportions were not correlated, suggesting that reduced funeral attendance and faster hospitalisation independently influenced local transmission intensity. We were able to identify 14% of potential source contacts as cases in the case line-list. Linking cases to the contacts who potentially infected them provided information on the transmission network. This revealed a high degree of heterogeneity in inferred transmissions, with only 20% of cases accounting for at least 73% of new infections, a phenomenon often called super-spreading. Multivariable regression models allowed us to identify predictors of being named as a potential source contact. These were similar for funeral and non-funeral contacts: severe symptoms, death, non-hospitalisation, older age, and travelling prior to symptom onset. Non-funeral exposures were strongly peaked around the death of the contact. There was evidence that hospitalisation reduced but did not eliminate onward exposures. We found that Ebola treatment units were better than other health care facilities at preventing exposure from hospitalised and deceased individuals. The principal limitation of our analysis is limited data quality, with cases not being entered into the database, cases not reporting exposures, or data being entered incorrectly (especially dates, and possible misclassifications). Conclusions Achieving elimination of Ebola is challenging, partly because of super-spreading. Safe funeral practices and fast hospitalisation contributed to the containment of this Ebola epidemic. Continued real-time data capture, reporting, and analysis are vital to track transmission patterns, inform resource deployment, and thus hasten and maintain elimination of the virus from the human population., In this retrospective observational study, Christophe Fraser and colleagues analyze the exposure patterns associated with Ebola transmission during the 2013-2016 epidemic in West Africa., Author Summary Why Was This Study Done? Knowing how and from whom individuals acquire infection can help inform the response to limit the impact of an epidemic; this study presents updated versions of analyses initially performed to assist the international response during the 2013–2016 Ebola epidemic in West Africa. Over 19,000 individuals with confirmed or probable Ebola (“cases”) were reported in West Africa by 4 May 2015. Cases were asked whether they had exposure to potential Ebola cases (“potential source contacts”) in a funeral or non-funeral context prior to becoming ill. What Did the Researchers Do and Find? We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. Non-funeral exposures were strongly peaked around the time of death of the contact. There was evidence of super-spreading, with only 20% of cases accounting for at least 73% of new infections. What Do These Findings Mean? Safe funeral practices and fast hospitalisation contributed to the containment of this Ebola epidemic. The data are highly detailed despite the challenging circumstances in the three countries; however, the analyses were limited by data quality, mostly missing data and incorrect entries. In light of viral persistence in reservoirs, it is vital to maintain active surveillance and analysis of Ebola outbreaks to avoid and contain future outbreaks.

CONSISE - The consortium for the Standardization of Influenza Seroepidemiology - is a global partnership to develop influenza investigation protocols and standardize seroepidemiology to inform health policy. This international partnership was formed in 2011 and was created out of a need, identified during the 2009 H1N1 pandemic, for timely seroepidemiological data to better estimate pandemic virus infection severity and attack rates to inform policy decisions. CONSISE has developed into a consortium of two interactive working groups: epidemiology and laboratory, with a steering committee composed of individuals from several organizations. CONSISE has had two international meetings with more planned for 2013. We seek additional members from public health agencies, academic institutions and other interested parties.

Accurate estimates of disease burden are possible by building high-resolution geographical models. However, novel pathogens such as Zika virus pose substantial challenges, requiring both new analytical techniques and, where possible, serological surveys.

Between December 2013 and April 2016, the largest epidemic of Ebola virus disease (EVD) to date generated more than 28,000 cases and more than 11,000 deaths in the large, mobile populations of Guinea, Liberia, and Sierra Leone. Tracking the rapid rise and slower decline of the West African epidemic has reinforced some common understandings about the epidemiology and control of EVD but has also generated new insights. Despite having more information about the geographic distribution of the disease, the risk of human infection from animals and from survivors of EVD remains unpredictable over a wide area of equatorial Africa. Until human exposure to infection can be anticipated or avoided, future outbreaks will have to be managed with the classic approach to EVD control — extensive surveillance, rapid detection and diagnosis, comprehensive tracing of contacts, prompt patient isolation, supportive clinical care, rigorous efforts to prevent and control infection, safe and dignified burial, and engagement of the community. Empirical and modeling studies conducted during the West African epidemic have shown that large epidemics of EVD are preventable — a rapid response can interrupt transmission and restrict the size of outbreaks, even in densely populated cities. The critical question now is how to ensure that populations and their health services are ready for the next outbreak, wherever it may occur. Health security across Africa and beyond depends on committing resources to both strengthen national health systems and sustain investment in the next generation of vaccines, drugs, and diagnostics.

International audience; BACKGROUND: The global impact of the 2009 influenza A(H1N1) pandemic (H1N1pdm) is not well understood. OBJECTIVES: We estimate overall and age-specific prevalence of cross-reactive antibodies to H1N1pdm virus and rates of H1N1pdm infection during the first year of the pandemic using data from published and unpublished H1N1pdm seroepidemiological studies.METHODS: Primary aggregate H1N1pdm serologic data from each study were stratified in standardized age groups and evaluated based on when sera were collected in relation to national or subnational peak H1N1pdm activity. Seropositivity was assessed using well-described and standardized hemagglutination inhibition (HI titers ≥ 32 or ≥ 40) and microneutralization (MN ≥ 40) laboratory assays. The prevalence of cross-reactive antibodies to the H1N1pdm virus was estimated for studies using sera collected prior to the start of the pandemic (between 2004 and April 2009); H1N1pdm cumulative incidence was estimated for studies in which collected both pre- and post-pandemic sera; and H1N1pdm seropositivity was calculated from studies with post-pandemic sera only (collected between December 2009-June 2010).RESULTS: Data from 27 published/unpublished studies from 19 countries/administrative regions - Australia, Canada, China, Finland, France, Germany, Hong Kong SAR, India, Iran, Italy, Japan, Netherlands, New Zealand, Norway, Reunion Island, Singapore, United Kingdom, United States, and Vietnam - were eligible for inclusion. The overall age-standardized pre-pandemic prevalence of cross-reactive antibodies was 5% (95%CI 3-7%) and varied significantly by age with the highest rates among persons ≥ 65 years old (14% 95%CI 8-24%). Overall age-standardized H1N1pdm cumulative incidence was 24% (95%CI 20-27%) and varied significantly by age with the highest in children 5-19 (47% 95%CI 39-55%) and 0-4 years old (36% 95%CI 30-43%).CONCLUSIONS: Our results offer unique insight into the global impact of the H1N1 pandemic and highlight the need for standardization of seroepidemiological studies and for their inclusion in pre-pandemic preparedness plans. Our results taken together with recent global pandemic respiratory-associated mortality estimates suggest that the case fatality ratio of the pandemic virus was approximately 0.02%.

With more than 1,700 laboratory-confirmed infections, Middle East respiratory syndrome coronavirus (MERS-CoV) remains a significant threat for public health. However, the lack of detailed data on modes of transmission from the animal reservoir and between humans means that the drivers of MERS-CoV epidemics remain poorly characterized. Here, we develop a statistical framework to provide a comprehensive analysis of the transmission patterns underlying the 681 MERS-CoV cases detected in the Kingdom of Saudi Arabia (KSA) between January 2013 and July 2014. We assess how infections from the animal reservoir, the different levels of mixing, and heterogeneities in transmission have contributed to the buildup of MERS-CoV epidemics in KSA. We estimate that 12% [95% credible interval (CI): 9%, 15%] of cases were infected from the reservoir, the rest via human-to-human transmission in clusters (60%; CI: 57%, 63%), within (23%; CI: 20%, 27%), or between (5%; CI: 2%, 8%) regions. The reproduction number at the start of a cluster was 0.45 (CI: 0.33, 0.58) on average, but with large SD (0.53; CI: 0.35, 0.78). It was >1 in 12% (CI: 6%, 18%) of clusters but fell by approximately one-half (47% CI: 34%, 63%) its original value after 10 cases on average. The ongoing exposure of humans to MERS-CoV from the reservoir is of major concern, given the continued risk of substantial outbreaks in health care systems. The approach we present allows the study of infectious disease transmission when data linking cases to each other remain limited and uncertain.

Please cite this paper as: Laurie et al. (2013) Influenza serological studies to inform public health action: best practices to optimise timing, quality and reporting. Influenza and Other Respiratory Viruses 7(2) 211–224. Background Serological studies can detect infection with a novel influenza virus in the absence of symptoms or positive virology, providing useful information on infection that goes beyond the estimates from epidemiological, clinical and virological data. During the 2009 A(H1N1) pandemic, an impressive number of detailed serological studies were performed, yet the majority of serological data were available only after the first wave of infection. This limited the ability to estimate the transmissibility and severity of this novel infection, and the variability in methodology and reporting limited the ability to compare and combine the serological data. Objectives To identify best practices for conduct and standardisation of serological studies on outbreak and pandemic influenza to inform public policy. Methods/Setting An international meeting was held in February 2011 in Ottawa, Canada, to foster the consensus for greater standardisation of influenza serological studies. Results Best practices for serological investigations of influenza epidemiology include the following: classification of studies as pre-pandemic, outbreak, pandemic or inter-pandemic with a clearly identified objective; use of international serum standards for laboratory assays; cohort and cross-sectional study designs with common standards for data collection; use of serum banks to improve sampling capacity; and potential for linkage of serological, clinical and epidemiological data. Advance planning for outbreak studies would enable a rapid and coordinated response; inclusion of serological studies in pandemic plans should be considered. Conclusions Optimising the quality, comparability and combinability of influenza serological studies will provide important data upon emergence of a novel or variant influenza virus to inform public health action.

As of November 2015, the Ebola virus disease (EVD) epidemic that began in West Africa in late 2013 is waning. The human toll includes more than 28,000 EVD cases and 11,000 deaths in Guinea, Liberia, and Sierra Leone, the most heavily-affected countries. We reviewed 66 mathematical modeling studies of the EVD epidemic published in the peer-reviewed literature to assess the key uncertainties models addressed, data used for modeling, public sharing of data and results, and model performance. Based on the review, we suggest steps to improve the use of modeling in future public health emergencies. DOI: http://dx.doi.org/10.7554/eLife.09186.001, eLife digest The outbreak of Ebola that started in West Africa in late 2013 has caused at least 28,000 illnesses and 11,000 deaths. As the outbreak progressed, global and local public health authorities scrambled to contain the spread of the disease by isolating those who were ill, putting in place infection control processes in health care settings, and encouraging the public to take steps to prevent the spread of the illness in the community. It took a massive investment of resources and personnel from many countries to eventually bring the outbreak under control. To determine where to allocate people and resources during the outbreak, public health authorities often turned to mathematical models created by scientists to predict the course of the outbreak and identify interventions that could be effective. Many groups of scientists created models of the epidemic using publically available data or data they obtained from government officials or field studies. In some instances, the models yielded valuable insights. But with various groups using different methods and data, the models didn’t always agree on what would happen next or how best to contain the epidemic. Now, Chretien et al. provide an overview of Ebola mathematical modeling during the epidemic and suggest how future efforts may be improved. The overview included 66 published studies about Ebola outbreak models. Although most forecasts predicted many more cases than actually occurred, some modeling approaches produced more accurate predictions, and several models yielded valuable insights. For example, one study found that focusing efforts on isolating patients with the most severe cases of Ebola would help end the epidemic by substantially reducing the number of new infections. Another study used real-time airline data to predict which traveler screening strategies would be most efficient at preventing international spread of Ebola. Furthermore, studies that obtained genomic data showed how specific virus strains were transmitted across geographic areas. Chretien et al. argue that mathematical modeling efforts could be more useful in future pubic health emergencies if modelers cooperated more, and suggest the collaborative approach of weather forecasters as a good example to follow. Greater data sharing and the creation of standards for epidemic modeling would aid better collaboration. DOI: http://dx.doi.org/10.7554/eLife.09186.002

Ebola emerged in West Africa around December 2013 and swept through Guinea, Sierra Leone and Liberia, giving rise to 27,748 confirmed, probable and suspected cases reported by 29 July 2015. Case diagnoses during the epidemic have relied on polymerase chain reaction-based tests. Owing to limited laboratory capacity and local transport infrastructure, the delays from sample collection to test results being available have often been 2 days or more. Point-of-care rapid diagnostic tests offer the potential to substantially reduce these delays. We review Ebola rapid diagnostic tests approved by the World Health Organization and those currently in development. Such rapid diagnostic tests could allow early triaging of patients, thereby reducing the potential for nosocomial transmission. In addition, despite the lower test accuracy, rapid diagnostic test-based diagnosis may be beneficial in some contexts because of the reduced time spent by uninfected individuals in health-care settings where they may be at increased risk of infection; this also frees up hospital beds. We use mathematical modelling to explore the potential benefits of diagnostic testing strategies involving rapid diagnostic tests alone and in combination with polymerase chain reaction testing. Our analysis indicates that the use of rapid diagnostic tests with sensitivity and specificity comparable with those currently under development always enhances control, whether evaluated at a health-care-unit or population level. If such tests had been available throughout the recent epidemic, we estimate, for Sierra Leone, that their use in combination with confirmatory polymerase chain-reaction testing might have reduced the scale of the epidemic by over a third.

Aims: Microbial contamination of powdered infant formula (PIF) is known to cause gastrointestinal infections in infants. Of concern is intrinsic contamination of the formula with (for example) Salmonella enterica as well as extrinsic contamination from inappropriate handling or ineffective disinfection. The aim of this study was to evaluate organic and microbial contamination of `in-use' bottles used for feeding infants powdered formula milk in South Wales, UK. Methods: To establish baseline contamination levels of `in-use' bottles, 75 `uncleaned' and 150 `cleaned and ready to re-use' bottles used for feeding infants PIF were analyzed. The microbiological analysis included aerobic colony counts (ACCs), presence/absence and counts of Enterobacteriaceae and Staphylococcus aureus. The level of residual adenosine tri-phosphate (ATP) was determined as an indicator of organic soiling. All bottles were sampled in four sites; inner screwcap, bottle interior; bottle outer rim and teat interior. Results: Microbial counts up to 105/area were sampled and ATP levels up to 100,051 relative light units (RLUs) were obtained from `uncleaned' bottles. Findings varied according to bottle site. Enterobacteriaceae and Staphylococcus aureus were isolated from 12—15% of `unclean' bottles/components (up to 102 cfu/area sampled) and contamination was most frequently detected from the screw cap and teat interiors. Data indicated that after use, prior to cleaning, considerable microbial and organic soil remained in the cumulative bottles. Of the ready-to-use bottles reportedly cleaned and disinfected, some had ACCs up to 5.8x104 cfu/area sampled. Staphylococcus aureus was detected from 4% bottles/components but no Enterobacteriaceae were detected. Conclusions: Cumulatively, findings indicate the presence of organic soiling and the potential for survival of bacteria between infant feeds. There is a need for effective education on effective bottle decontamination procedures. This may be achieved by using an audience-centred approach to re-enforce messages to parents and caregivers to implement good hygiene practices, effectively wash and rinse items before disinfection and follow manufacturers' guidelines for disinfection.

Background Hyperplastic granular gingivitis or “strawberry gingivitis” is a rare manifestation of Wegener's granulomatosis (WG), but it is nearly pathognomonic for this multisystem autoimmune vasculitis. The dentist may be the first health care professional to see patients with symptoms and findings of this condition. Early diagnosis and treatment is the most important factor in the management of this potentially fatal disease. Methods The authors present three case reports that demonstrate the disease spectrum and conducted a literature review focused on current understanding of this disease. Results The first patient had only the classic gingival manifestations of the disease. The second patient had simultaneous typical gingival lesions, as well as dermatologic findings. The third patient had an atypical oral presentation of aphthous ulcers and erythematous gingiva, as well as respiratory and genital involvement. Reaching a definitive diagnosis sometimes is challenging owing to the subtle onset of the disease and variable clinical and laboratory findings. Conclusion and Clinical Implications Clinicians should be familiar with the broad variety of oral and systemic components of WG, as well as strategies to facilitate prompt disease recognition and to provide continued oral health care to these medically complex patients.

Background Until recently, oesophagectomy was the treatment of choice for early oesophageal cancer. Endoscopic treatment has been introduced relatively recently. This observational national database study aimed to describe how endoscopic therapy has been introduced in England and to examine the safety of this approach. Methods A population-based cohort study was undertaken of patients diagnosed with oesophageal adenocarcinoma between October 2007 and June 2009 using three linked national databases. Patients with early-stage disease (T1 tumours with no evidence of spread) were identified, along with the primary treatment modality where treatment intent was curative. Short-term outcomes after treatment and 5-year survival were evaluated. Results Of 5192 patients diagnosed with oesophageal adenocarcinoma, 306 (5·9 per cent) were considered to have early-stage disease before any treatment, of whom 239 (79·9 per cent of 299 patients with data on treatment intent) were managed with curative intent. Of 175 patients who had an oesophagectomy, 114 (65·1 (95 per cent c.i. 57·6 to 72·7) per cent) survived for 5 years. Among these, 47 (30·3 per cent of 155 patients with tissue results available) had their disease upstaged after pathological staging; this occurred more often in patients who did not have staging endoscopic ultrasonography before surgery. Of 41 patients who had an endoscopic resection, 27 (66 (95 per cent c.i. 49 to 80) per cent) survived for 5 years. Repeat endoscopic therapy was required by 23 (56 per cent) of these 41 patients. Conclusion Between 2007 and 2009, oesophagectomy remained the initial treatment of choice (73·2 per cent) among patients with early-stage oesophageal cancer treated with curative intent; one in five patients were managed endoscopically, and this treatment was more common in elderly patients. Although the groups had different patient characteristics, 5-year survival rates were similar.

Background The progression from hospitalization for a respiratory infection to requiring substantial supportive therapy is a key stage of the influenza severity pyramid. Respiratory infections are responsible for 300,000–400,000 medical encounters each year among US military personnel, some of which progress to severe acute respiratory infections. Methods We obtained data on 11,086 hospitalizations for pneumonia and influenza (P&I) among non-recruit US military service members during the period of 1 January 2000 through 31 December 2012. From these, we identified 512 P&I hospitalizations that progressed to severe episodes using standard case definitions. We evaluated the effect of demographic and occupational characteristics, co-morbid conditions, and history of influenza vaccination on the risk of a hospitalized P&I case becoming a severe case. We also evaluated the risk of a severe outcome and the length of time since influenza vaccination (within 180, 60, and 30 days). Results The median age of subjects at the time of the P&I episode was 32 years (range, 28–40) and subjects were predominantly male (89.5%). In a univariate analysis, demographic risk factors for a severe episode included service in the US Air Force (RR = 1.6 relative to US Army, 95%CI 1.3–2.1), US Coast Guard (RR = 2.1, 1.2–3.7) or US Navy (RR = 1.4, 1.1–1.8). Being born in the US and recent influenza vaccination (within 180 days of episode) were protective against developing severe disease. Among co-morbid conditions, univariate risk factors for severe disease included chronic renal or liver disease (RR = 4.98, 95%CI 4.1–6.1), diseases of the circulatory system (RR = 3.1, 95%CI 2.6–3.7), diabetes mellitus (RR = 2.3, 95%CI 1.5–3.6), obesity (RR = 1.6, 95%CI 1.2–2.1), cancer (RR = 1.6, 95%CI 1.3–2.0), and chronic obstructive pulmonary disease (RR = 1.4, 95%CI 1.1–1.7). Although many of the risk factors found to be significant in univariate analysis were no longer significant under a multivariate analysis, receipt of any influenza vaccine within 180 days of episode remained protective (RR = 0.81, 95%CI 0.67–0.99), while serving in the US Coast Guard (RR = 1.9, 95%CI 1.1–3.4) or US Air Force (RR = 1. 5, 95%CI 1.2–2.0), presence of renal or liver disease (RR = 3.6, 95%CI 2.9–4.6), and diseases of the circulatory system (RR = 2.2, 95%CI 1.8–2.8), remained significantly associated with a higher risk of developing severe disease. Conclusions In a large cohort, after adjusting for many possible risk factors, influenza vaccination was protective against severe episodes among P&I hospitalizations. The service-specific (US Coast Guard or US Air Force) increased risk may represent some differences in data (e.g., coding or reporting practices) as opposed to genuine differences in physiological outcome. Our findings suggest that renal and liver disease as well as diseases of the circulatory system may contribute to influenza severity in this population independently of age and other potential comorbidities. These findings provide additional evidence for the prioritization of specific risk groups within the US military for influenza vaccination

Ebola virus has caused substantial illness in West Africa in the past year. In this report, the burden of illness in children is described.

Contingency planning for the possible deliberate reintroduction of smallpox has become a priority for many national public health organizations in recent years. We used an individual-based spatial model of smallpox transmission in Great Britain and census-derived journey-to-work data to accurately describe the spatiotemporal dynamics of an outbreak of smallpox in the community. A Markov chain Monte-Carlo algorithm was developed to generate sociospatial contact networks that were consistent with demographic and commuting data. We tested the sensitivity of model predictions to key epidemiological parameters before choosing three representative scenarios from within the range explored. We examined the spatiotemporal dynamics for these illustrative scenarios and assessed the efficacy of symptomatic case isolation, contact tracing with vaccination, and reactive regional mass vaccination as policy options for control. We conclude that case isolation and contact tracing with vaccination would be sufficient to halt ongoing transmission rapidly, unless policy effectiveness was compromised by resource or other constraints. A slight reduction in the expected size and duration of an outbreak could be achieved with regional mass vaccination, but these benefits are small and do not justify the high numbers of vaccine doses required and their associated negative side effects.

Assessing the pandemic risk posed by specific non-human influenza A viruses is an important goal in public health research. As influenza virus genome sequencing becomes cheaper, faster, and more readily available, the ability to predict pandemic potential from sequence data could transform pandemic influenza risk assessment capabilities. However, the complexities of the relationships between virus genotype and phenotype make such predictions extremely difficult. The integration of experimental work, computational tool development, and analysis of evolutionary pathways, together with refinements to influenza surveillance, has the potential to transform our ability to assess the risks posed to humans by non-human influenza viruses and lead to improved pandemic preparedness and response. DOI: http://dx.doi.org/10.7554/eLife.03883.001